SPAAC Pulse-Chase: A Novel Click Chemistry-Based Method to Determine the Half-Life of Cellular Proteins
Bibliographic record
Abstract
Assessing the stability and degradation of proteins is central to the study of cellular biological processes. Here, we describe a novel pulse-chase method to determine the half-life of cellular proteins that overcomes the limitations of other commonly used approaches. This method takes advantage of pulse-labeling of nascent proteins in living cells with the bioorthogonal amino acid L-azidohomoalanine (AHA) that is compatible with click chemistry-based modifications. We validate this method in both mammalian and yeast cells by assessing both over-expressed and endogenous proteins using various fluorescent and chemiluminescent click chemistry-compatible probes. Importantly, while cellular stress responses are induced to a limited extent following live-cell AHA pulse-labeling, we also show that this response does not result in changes in cell viability and growth. Moreover, this method is not compromised by the cytotoxicity evident in other commonly used protein half-life measurement methods and it does not require the use of radioactive amino acids. This new method thus presents a versatile, customizable, and valuable addition to the toolbox available to cell biologists to determine the stability of cellular proteins.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".